An automated behavioral box to assess forelimb function in rats

Information flow between motor cortex and striatum reverses during skill learning

The coordination of neural activity across brain areas during a specific behavior is often interpreted as neural communication involved in controlling the behavior. However, whether information relevant to the behavior is actually transferred between areas is often untested. Here, we used information-theoretic tools to quantify how motor cortex and striatum encode and exchange behaviorally relevant information about specific reach-to-grasp movement features during skill learning in rats. We found a temporal shift in the encoding of behaviorally relevant information during skill learning, as well as a reversal in the primary direction of behaviorally relevant information flow, from cortex-to-striatum during naive movements to striatum-to-cortex during skilled movements. Standard analytical methods that quantify the evolution of overall neural activity during learning-such as changes in neural signal amplitude or the overall exchange of information between areas-failed to capture these behaviorally relevant information dynamics. Using these standard methods, we instead found a consistent coactivation of overall neural signals during movement production and a bidirectional increase in overall information propagation between areas during learning. Our results show that skill learning is achieved through a transformation in how behaviorally relevant information is routed across cortical and subcortical brain areas and that isolating the components of neural activity relevant to and informative about behavior is critical to uncover directional interactions within a coactive and coordinated network.

Modulation of neural spiking in motor cortex-cerebellar networks during sleep spindles

Sleep spindles appear to play an important role in learning new motor skills. Motor skill learning engages several regions in the brain with two important areas being the motor cortex (M1) and the cerebellum. However, the neurophysiological processes in these areas during sleep, especially how spindle oscillations affect local and cross-region spiking, are not fully understood. We recorded activity from the M1 and cerebellar cortex in 8 rats during spontaneous activity to investigate how sleep spindles in these regions are related to local spiking as well as cross-region spiking. We found that M1 firing was significantly changed during both M1 and cerebellum spindles and this spiking occurred at a preferred phase of the spindle. On average, M1 and cerebellum neurons showed most spiking at the M1 or cerebellum spindle peaks. These neurons also developed a preferential phase-locking to local or cross-area spindles with the greatest phase-locking value at spindle peaks; however, this preferential phase-locking wasn't significant for cerebellar neurons when compared to cerebellum spindles. Additionally, we found the percentage of task-modulated cells in the M1 and cerebellum that fired with non-uniform spike-phase distribution during M1/ cerebellum spindle peaks were greater in the rats that learned a reach-to-grasp motor task robustly. Finally, we found that spindle-band LFP coherence (for M1 and cerebellum LFPs) showed a positive correlation with success rate in the motor task. These findings support the idea that sleep spindles in both the M1 and cerebellum recruit neurons that participate in the awake task to support motor memory consolidation.Significance Statement Neural processing during sleep spindles is linked to memory consolidation. However, little is known about sleep activity in the cerebellum and whether cerebellum spindles can affect spiking activity in local or distant areas. We report the effect of sleep spindles on neuron activity in the M1 and cerebellum-specifically their firing rate and phase-locking to spindle oscillations. Our results indicate that awake practice neuronal activity is tempered during local M1 and cerebellum spindles, and during cross-region spindles, which may support motor skill learning. We describe spiking dynamics in motor networks spindle oscillations that may aid in the learning of skills. Our results support the sleep reactivation hypothesis and suggest that awake M1 activity may be reactivated during cerebellum spindles.

Emergence of task-related spatiotemporal population dynamics in transplanted neurons

Loss of nervous system tissue after severe brain injury is a main determinant of poor functional recovery. Cell transplantation is a promising method to restore lost tissue and function, yet it remains unclear if transplanted neurons can demonstrate the population level dynamics important for movement control. Here we present a comprehensive approach for long-term single neuron monitoring and manipulation of transplanted embryonic cortical neurons after cortical injury in adult male mice performing a prehension task. The observed patterns of population activity in the transplanted network strongly resembled that of healthy networks. Specifically, the task-related spatiotemporal activity patterns of transplanted neurons could be represented by latent factors that evolve within a low dimensional manifold. We also demonstrate reliable modulation of the transplanted networks using minimally invasive epidural stimulation. Our approach may allow greater insight into how restoration of cell-type specific network dynamics in vivo can restore motor function.

Emergence of preparatory dynamics in VIP interneurons during motor learning

To determine what actions to perform in each context, animals must learn how to execute motor programs in response to sensory cues. In rodents, the interface between sensory processing and motor planning occurs in the secondary motor cortex (M2). Here, we investigate dynamics in vasointestinal peptide (VIP) and somatostatin (SST) interneurons in M2 during acquisition of a cue-based, reach-to-grasp (RTG) task in mice. We observe the emergence of preparatory activity consisting of sensory responses and ramping activation in a subset of VIP interneurons during motor learning. We show that preparatory and movement activities in VIP neurons exhibit compartmentalized dynamics, with principal component 1 (PC1) and PC2 reflecting primarily movement and preparatory activity, respectively. In contrast, we observe later and more synchronous activation of SST neurons during the movement epoch with learning. Our results reveal how VIP population dynamics might support sensorimotor learning and compartmentalization of sensory processing and movement execution.

AutoRG: An automatized reach-to-grasp platform technology for assessing forelimb motor function, neural circuit activation, and cognition in rodents

BACKGROUND

Rodent reach-to-grasp function assessment is a translationally powerful model for evaluating neurological function impairments and recovery responses. Existing assessment platforms are experimenter-dependent, costly, or low-throughput with limited output measures. Further, a direct histologic comparison of neural activation has never been conducted between any novel, automated platform and the well-established single pellet skilled reach task (SRT).

NEW METHOD

To address these technological and knowledge gaps, we designed an open-source, low-cost Automatized Reach-to-Grasp (AutoRG) pull platform that reduces experimenter interventions and variability. We assessed reach-to-grasp function in rats across seven progressively difficult stages using AutoRG. We mapped AutoRG and SRT-activated motor circuitries in the rat brain using volumetric imaging of the immediate early gene-encoded Arc (activity-regulated cytoskeleton-associated) protein.

RESULTS

Rats demonstrated robust forelimb reaching and pulling behavior after training in AutoRG. Reliable force versus time responses were recorded for individual reach events in real time, which were used to derive several secondary functional measures of performance. Moreover, we provide the first demonstration that for a training period of 30 min, AutoRG and SRT both engage similar neural responses in the caudal forelimb area (CFA), rostral forelimb area (RFA), and sensorimotor area (S1).

CONCLUSION

AutoRG is the first low-cost, open-source pull system designed for the scale-up of volitional forelimb motor function testing and characterization of rodent reaching behavior. The similarities in neuronal activation patterns observed in the rat motor cortex after SRT and AutoRG assessments validate the AutoRG as a rigorously characterized, scalable alternative to the conventional SRT and expensive commercial systems.

Using Operant Reach Chambers to Assess Mouse Skilled Forelimb Use After Stroke

Skilled forelimb reaching and grasping are important components of rodent motor performance. The isometric pull task can serve as a tool for quantifying forelimb function following stroke or other CNS injury as well as in forelimb rehabilitation. This task has been extensively developed for use in rats. Here, we describe methods of setup and training of an operant reach chamber for mice. Using a reward of peanut oil, mice are adaptively trained to pull a handle positioned slightly outside of an operant chamber, with automated recording of the number of attempts, force generated, success rate, and latency to maximal force.

Emergent Low-Frequency Activity in Cortico-Cerebellar Networks with Motor Skill Learning

The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex (M1) is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats, which revealed the emergence of coordinated movement-related activity in the local-field potentials as the reaching skill consolidated. Interestingly, we found this emergent activity only in the rats that gained expertise in the task. We found that the local and cross-area spiking activity was coordinated with LFOs in proficient rats. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior in the M1. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.

Cortical-hippocampal coupling during manifold exploration in motor cortex

Systems consolidation-a process for long-term memory stabilization-has been hypothesized to occur in two stages1-4. Whereas new memories require the hippocampus5-9, they become integrated into cortical networks over time10-12, making them independent of the hippocampus. How hippocampal-cortical dialogue precisely evolves during this and how cortical representations change in concert is unknown. Here, we use a skill learning task13,14 to monitor the dynamics of cross-area coupling during non-rapid eye movement sleep along with changes in primary motor cortex (M1) representational stability. Our results indicate that precise cross-area coupling between hippocampus, prefrontal cortex and M1 can demarcate two distinct stages of processing. We specifically find that each animal demonstrates a sharp increase in prefrontal cortex and M1 sleep slow oscillation coupling with stabilization of performance. This sharp increase then predicts a drop in hippocampal sharp-wave ripple (SWR)-M1 slow oscillation coupling-suggesting feedback to inform hippocampal disengagement and transition to a second stage. Notably, the first stage shows significant increases in hippocampal SWR-M1 slow oscillation coupling in the post-training sleep and is closely associated with rapid learning and variability of the M1 low-dimensional manifold. Strikingly, even after consolidation, inducing new manifold exploration by changing task parameters re-engages hippocampal-M1 coupling. We thus find evidence for dynamic hippocampal-cortical dialogue associated with manifold exploration during learning and adaptation.

Improved Behavioral Box and Sensing Techniques for Analysis of Tactile Discrimination Tasks in Rodents

Neuroscience behavioral studies stand out among the research works in this area. In these studies, normally, rodents are put inside closed platforms known as behavioral boxes in order to perform tasks and have their behaviors observed by way of sensors and annotations by hand. In this work, we aim to improve this research process by developing new techniques based upon the full automation of the behavioral box processes for more easily acquiring data. We come up with a new structural design using cutting-edge technology, with enhanced spaces and better materials. We use components that can be easily purchased (or built) and developed new techniques for control and data acquisition. Our new platform allows for more precise control of the opening of the discrimination bars, which was not satisfactorily done with previous platforms. This makes possible the design of more complex decision-making experiments using camera and sensor systems, allowing a better assessment of rodent performance in the discrimination task. All the necessary materials and development documents are made available in a collaborative multi-user platform allowing work replication. With this, the present study provides a low-cost tool with ease of development and construction that can be used by laboratories that work with this type of research.

Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration

Animals can capitalize on invariance in the environment by learning and automating highly consistent actions; however, they must also remain flexible and adapt to environmental changes. It remains unclear how primary motor cortex (M1) can drive precise movements, yet also support behavioral exploration when faced with consistent errors. Using a reach-to-grasp task in rats, along with simultaneous electrophysiological monitoring in M1 and dorsolateral striatum (DLS), we find that behavioral exploration to overcome consistent task errors is closely associated with tandem increases in M1 and DLS neural variability; subsequently, consistent ensemble patterning returns with convergence to a new successful strategy. We also show that compared to reliably patterned intracranial microstimulation in M1, variable stimulation patterns result in significantly greater movement variability. Our results thus indicate that motor and striatal areas can flexibly transition between two modes, reliable neural pattern generation for automatic and precise movements versus variable neural patterning for behavioral exploration.

It is not fully understood how behavioral flexibility is established in the context of automatic performance of a complex motor skill. Here the authors show that corticostriatal activity can flexibly transition between two modes during a reach to-grasp task in rats: reliable neural pattern generation for precise, automatic movements versus variable neural patterning for behavioral exploration.

Recovery of consolidation after sleep following stroke-interaction of slow waves, spindles, and GABA

Sleep is known to promote recovery after stroke. Yet it remains unclear how stroke affects neural processing during sleep. Using an experimental stroke model in rats along with electrophysiological monitoring of neural firing and sleep microarchitecture, here we show that sleep processing is altered by stroke. We find that the precise coupling of spindles to global slow oscillations (SOs), a phenomenon that is known to be important for memory consolidation, is disrupted by a pathological increase in "isolated" local delta waves. The transition from this pathological to a physiological state-with increased spindle coupling to SO-is associated with sustained performance gains during recovery. Interestingly, post-injury sleep could be pushed toward a physiological state via a pharmacological reduction of tonic γ-aminobutyric acid (GABA). Together, our results suggest that sleep processing after stroke is impaired due to an increase in delta waves and that its restoration can be important for recovery.

Evolution of Gross Forelimb and Fine Digit Kinematics during Skilled Reaching Acquisition in Rats

The ability to learn dexterous motor skills is a fundamental aspect of human behavior. However, the underlying neural circuit mechanisms for dexterous skill learning are unclear. Advancing our understanding of motor skill learning requires the integration of modern neuroscientific techniques with a rigorously characterized dexterous task. The development of automated rodent skilled reaching with paw tracking allows detailed analysis of how reach-to-grasp kinematics evolve during learning. We assessed how both "gross" forelimb and "fine" digit kinematics changed as rats learned skilled reaching. Rats whose success rates increased (learners) consistently reduced the variability in their reach trajectories. Refinement of fine digit control generally continued after consistency in gross hand transport to the pellet plateaued. Interestingly, most rats whose success rates did not increase (non-learners) also converged on consistent reach kinematics. Some non-learners, however, maintained substantial variability in hand and digit trajectories throughout training. These results suggest that gross and fine motor components of dexterous skill are, on average, learned over different timescales. Nonetheless, there is significant intersubject variability in learning rates as assessed by both reaching success and consistency of reach kinematics.

Coupling between motor cortex and striatum increases during sleep over long-term skill learning

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or 'offline' during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-rapid-eye-movement (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements, and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

Coordinated increase of reliable cortical and striatal ensemble activations during recovery after stroke

Skilled movements rely on a coordinated cortical and subcortical network, but how this network supports motor recovery after stroke is unknown. Previous studies focused on the perilesional cortex (PLC), but precisely how connected subcortical areas reorganize and coordinate with PLC is unclear. The dorsolateral striatum (DLS) is of interest because it receives monosynaptic inputs from motor cortex and is important for learning and generation of fast reliable actions. Using a rat focal stroke model, we perform chronic electrophysiological recordings in motor PLC and DLS during long-term recovery of a dexterous skill. We find that recovery is associated with the simultaneous emergence of reliable movement-related single-trial ensemble spiking in both structures along with increased cross-area alignment of spiking. Our study highlights the importance of consistent neural activity patterns across brain structures during recovery and suggests that modulation of cross-area coordination can be a therapeutic target for enhancing motor function post-stroke.

The Home-Cage Automated Skilled Reaching Apparatus (HASRA): Individualized Training of Group-Housed Mice in a Single Pellet Reaching Task

The single pellet reaching task is commonly used in rodents to assess the acquisition of fine motor skill and recovery of function following nervous system injury. Although this task is useful for gauging skilled forelimb use in rodents, the process of training animals is labor intensive and variable across studies and labs. To address these limitations, we developed a single pellet reaching paradigm for training and testing group housed mice within their home cage. Mice enter a training compartment attached to the outside of the cage and retrieve millet seeds presented on a motorized pedestal that can be individually positioned to present seeds to either forelimb. To identify optimal training parameters, we compared task participation and success rates between groups of animals that were presented seeds at two different heights (floor vs mouth height) and at different intervals (fixed-time vs trial-based). The mouth height/fixed interval presentation style was most effective at promoting reaching behavior as all mice reached for seeds within 5 d. Using this paradigm, we assessed stroke-induced deficits in home-cage reaching. Following three weeks of baseline training, reaching success rate was ∼40%, with most trials performed during the dark cycle. A forelimb motor cortex stroke significantly decreased interaction with presented seeds within the first 2 d and impaired reaching success rates for the first 7 d. Our data demonstrate that group-housed mice can be efficiently trained on a single pellet reaching task in the home cage and that this assay is sensitive to stroke induced motor impairments.

Single-trial cross-area neural population dynamics during long-term skill learning

Mammalian cortex has both local and cross-area connections, suggesting vital roles for both local and cross-area neural population dynamics in cortically-dependent tasks, like movement learning. Prior studies of movement learning have focused on how single-area population dynamics change during short-term adaptation. It is unclear how cross-area dynamics contribute to movement learning, particularly long-term learning and skill acquisition. Using simultaneous recordings of rodent motor (M1) and premotor (M2) cortex and computational methods, we show how cross-area activity patterns evolve during reach-to-grasp learning in rats. The emergence of reach-related modulation in cross-area activity correlates with skill acquisition, and single-trial modulation in cross-area activity predicts reaction time and reach duration. Local M2 neural activity precedes local M1 activity, supporting top-down hierarchy between the regions. M2 inactivation preferentially affects cross-area dynamics and behavior, with minimal disruption of local M1 dynamics. Together, these results indicate that cross-area population dynamics are necessary for learned motor skills.

Chronic stability of single-channel neurophysiological correlates of gross and fine reaching movements in the rat

While substantial task-related neural activity has been observed during motor tasks in rodent primary motor cortex and premotor cortex, the long-term stability of these responses in healthy rats is uncertain, limiting the interpretability of longitudinal changes in the specific patterns of neural activity associated with learning or motor recovery following injury. This study examined the stability of task-related neural activity associated with execution of two distinct reaching tasks in healthy rodents. A novel automated rodent behavioral apparatus was constructed and rats were trained to perform a reaching task combining a ‘gross’ lever press and a ‘fine’ pellet retrieval. In each animal, two chronic microelectrode arrays were implanted in motor cortex spanning the caudal forelimb area (rodent primary motor cortex) and the rostral forelimb area (rodent premotor cortex). We recorded multiunit spiking and local field potential activity from 10 days to 7–10 weeks post-implantation to characterize the patterns of neural activity observed during each task component and analyzed the consistency of channel-specific task-related neural activity. Task-related changes in neural activity were observed on the majority of channels. While the task-related changes in multi-unit spiking and local field potential spectral power were consistent over several weeks, spectral power changes were more stable, despite the trade-off of decreased spatial and temporal resolution. These results show that neural activity in rodent primary and premotor cortex is associated with specific phases of reaching movements with stable patterns of task-related activity across time, establishing the relevance of the rodent for future studies designed to examine changes in task-related neural activity during recovery from focal cortical lesions.

A kinematic study of skilled reaching movement in rat

BACKGROUND

In the rat, the single-pellet reaching task includes orienting, reaching, grasping and retracting movements. It has previously been described by notation techniques, high-speed video and cineradiographic recordings. Recently, high-definition cameras have been used to track paw and digit movements with DeepLabCut, a machine-learning algorithm for markerless estimation of paw position.

NEW METHOD

Our new approach consists of positioning three high-speed infrared digital cameras to track the full motion of markers on the rat's body. This provided a previously unavailable 3D recording of skilled reaching kinematics in the rat moving freely in the reaching box, which were analysed by Qualisys Track Manager software and MATLAB.

RESULTS

This method enabled description of kinematic parameters unobtainable without motion tracking and provided insight into the spatiotemporal metrics of movements used to perform skilled reaching. It revealed that orientation features three steps and reaching has two bimodal start-point distributions, one along the horizontal axis and one along the vertical axis. At the end of reaching, the wrist/paw occupies the same position as the nose at the end of orienting. In grasping, averaging trajectories confirmed the marker lowering and target approaching.

COMPARISON WITH EXISTING METHODS

Our method required significantly reduced time to label data and obviates the need for off-line manual marking of videos. It provides an efficient means of capturing volumes containing the entire range of marker movements.

CONCLUSIONS

This study validated a new and efficient approach for quantifying rat movement kinematics, useful for comparing preclinical and clinical conditions.

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Rodent skilled reaching is commonly used to study dexterous skills, but requires significant time and effort to implement the task and analyze the behavior. Several automated versions of skilled reaching have been developed recently. Here, we describe a version that automatically presents pellets to rats while recording high-definition video from multiple angles at high frame rates (300 fps). The paw and individual digits are tracked with DeepLabCut, a machine learning algorithm for markerless pose estimation. This system can also be synchronized with physiological recordings, or be used to trigger physiologic interventions (e.g., electrical or optical stimulation).

Directional Reaching for Water as a Cortex-Dependent Behavioral Framework for Mice

Optogenetic tools and imaging methods for recording and manipulating brain activity have boosted the field of neuroscience in unprecedented ways. However, behavioral paradigms for mice lag behind those of primates, limiting the full potential of such tools. Here, we present an innovative behavioral framework in which head-fixed mice directionally reach for water droplets, similar to the primate "center-out" reaching task. Mice rapidly engaged in the task, performed hundreds of trials, and reached in multiple directions when droplets were presented at different locations. Surprisingly, mice used chemosensation to determine the presence of water droplets. Optogenetic inactivation of the motor cortex halted the initiation and rapidly diverted the trajectory of ongoing movements. Layer 2/3 two-photon imaging revealed robust direction selectivity in most reach-related neurons. Finally, mice performed directional reaching instructed by vibratotactile stimuli, demonstrating the potential of this framework for studying, in addition to motor control, sensory processing, and decision making.

Automated Forelimb Tasks for Rodents: Current Advantages and Limitations, and Future Promise

Rodent tests of function have advanced our understanding of movement, largely through the human training and testing and manual assessment. Tools such as reaching and grasping of a food pellet have been widely adopted because they are effective and simple to use. However, these tools are time-consuming, subjective, and often qualitative. Automation of training, testing, and assessment has the potential to increase efficiency while ensuring tasks are objective and quantitative. We detail new methods for automating rodent forelimb tests, including the use of pellet dispensers, sensors, computer vision, and home cage systems. We argue that limitations in existing forelimb tasks are driving the innovations in automated systems. We further argue that automated tasks partially address these limitations, and we outline necessary precautions and remaining challenges when adopting these types of tasks. Finally, we suggest attributes of future automated rodent assessment tools that can enable widespread adoption and help us better understand forelimb function in health and disease.

Emergent modular neural control drives coordinated motor actions

A remarkable feature of motor control is the ability to coordinate movements across distinct body parts into a consistent, skilled action. To reach and grasp an object, 'gross' arm and 'fine' dexterous movements must be coordinated as a single action. How the nervous system achieves this coordination is currently unknown. One possibility is that, with training, gross and fine movements are co-optimized to produce a coordinated action; alternatively, gross and fine movements may be modularly refined to function together. To address this question, we recorded neural activity in the primary motor cortex and dorsolateral striatum during reach-to-grasp skill learning in rats. During learning, the refinement of fine and gross movements was behaviorally and neurally dissociable. Furthermore, inactivation of the primary motor cortex and dorsolateral striatum had distinct effects on skilled fine and gross movements. Our results indicate that skilled movement coordination is achieved through emergent modular neural control.

Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation.

Automated Assessment of Endpoint and Kinematic Features of Skilled Reaching in Rats

Background: Neural injury to the motor cortex may result in long-term impairments. As a model for human impairments, rodents are often used to study deficits related to reaching and grasping, using the single-pellet reach-to-grasp task. Current assessments of this test capture mostly endpoint outcome. While qualitative features have been proposed, they usually involve manual scoring.

Objective: To detect three phases of movement during the single-pellet reach-to-grasp test and assess completion of each phase. To automatically monitor rat forelimb trajectory so as to extract kinematics and classify phase outcome.

Methods: A top-view camera is used to monitor three rats during training, healthy and impaired testing, over 33 days. By monitoring the coordinates of the forelimb tip along with the position of the pellet, the algorithm divides a trial into reaching, grasping and retraction. Unfulfilling any of the phases results in one of three possible errors: miss, slip or drop. If all phases are complete, the outcome label is success. Along with endpoints, movement kinematics are assessed: variability, convex hull, mean and maximum reaching speed, length of trajectory and peak forelimb extension.

Results: The set of behavior endpoints was extended to include miss, slip, drop and success rate. The labeling algorithm was tested on pre- and post-lesion datasets, with overall accuracy rates of 86% and 92%, respectively. These endpoint features capture a drop in skill after motor cortical lesion as the success rate of 59.6 ± 11.8% pre-lesion decreases to 13.9 ± 8.2% post-lesion, along with a significant increase in miss rate from 7.2 ± 6.7% pre-lesion to 50.2 ± 18.7% post-lesion. Kinematics reveals individual-specific strategies of improvement during training, with a common trend of trajectory variability decreasing with success. Correlations between kinematics and endpoints reveal a more complex pattern of relationships during rehabilitation (18 significant pairs of features) than during training (nine correlated pairs).

Conclusion: Extended endpoint outcomes and kinematics of reaching and grasping are captured automatically with a robust computer program. Both endpoints and kinematics capture intra-animal drop in skill after a motor cortical lesion. Correlations between kinematics and endpoints change from training to rehabilitation, suggesting different mechanisms that underlie motor improvement.

Individualized tracking of self-directed motor learning in group-housed mice performing a skilled lever positioning task in the home cage

Skilled forelimb function in mice is traditionally studied through behavioral paradigms that require extensive training by investigators and are limited by the number of trials individual animals are able to perform within a supervised session. We developed a skilled lever positioning task that mice can perform within their home cage. The task requires mice to use their forelimb to precisely hold a lever mounted on a rotary encoder within a rewarded position to dispense a water reward. A Raspberry Pi microcomputer is used to record lever position during trials and to control task parameters, thus making this low-footprint apparatus ideal for use within animal housing facilities. Custom Python software automatically increments task difficulty by requiring a longer hold duration, or a more accurate hold position, to dispense a reward. The performance of individual animals within group-housed mice is tracked through radio-frequency identification implants, and data stored on the microcomputer may be accessed remotely through an active internet connection. Mice continuously engage in the task for over 2.5 mo and perform ~500 trials/24 h. Mice required ~15,000 trials to learn to hold the lever within a 10° range for 1.5 s and were able to further refine movement accuracy by limiting their error to a 5° range within each trial. These results demonstrate the feasibility of autonomously training group-housed mice on a forelimb motor task. This paradigm may be used in the future to assess functional recovery after injury or cortical reorganization induced by self-directed motor learning. NEW & NOTEWORTHY We developed a low-cost system for fully autonomous training of group-housed mice on a forelimb motor task. We demonstrate the feasibility of tracking both end-point, as well as kinematic performance of individual mice, with each performing thousands of trials over 2.5 mo. The task is run and controlled by a Raspberry Pi microcomputer, which allows for cages to be monitored remotely through an active internet connection.

The Knob Supination Task: A Semi-automated Method for Assessing Forelimb Function in Rats

Tasks that accurately measure dexterity in animal models are critical to understand hand function. Current rat behavioral tasks that measure dexterity largely use video analysis of reaching or food manipulation. While these tasks are easy to implement and are robust across disease models, they are subjective and laborious for the experimenter. Automating traditional tasks or creating new automated tasks can make the tasks more efficient, objective, and quantitative. Since rats are less dexterous than primates, central nervous system (CNS) injury produces more subtle deficits in dexterity, however, supination is highly affected in rodents and crucial to hand function in primates. Therefore, we designed a semi-automated task that measures forelimb supination in rats. Rats are trained to reach and grasp a knob-shaped manipulandum and turn the manipulandum in supination to receive a reward. Rats can acquire the skill within 20 ± 5 days. While the early part of training is highly supervised, much of the training is done without direct supervision. The task reliably and reproducibly captures subtle deficits after injury and shows functional recovery that accurately reflects clinical recovery curves. Analysis of data is performed by specialized software through a graphical user interface that is designed to be intuitive. We also give solutions to common problems encountered during training, and show that minor corrections to behavior early in training produce reliable acquisition of supination. Thus, the knob supination task provides efficient and quantitative evaluation of a critical movement for dexterity in rats.

Dexterity: A MATLAB-based analysis software suite for processing and visualizing data from tasks that measure arm or forelimb function

BACKGROUND

Hand function is critical for independence, and neurological injury often impairs dexterity. To measure hand function in people or forelimb function in animals, sensors are employed to quantify manipulation. These sensors make assessment easier and more quantitative and allow automation of these tasks. While automated tasks improve objectivity and throughput, they also produce large amounts of data that can be burdensome to analyze. We created software called Dexterity that simplifies data analysis of automated reaching tasks.

NEW METHOD

Dexterity is MATLAB software that enables quick analysis of data from forelimb tasks. Through a graphical user interface, files are loaded and data are identified and analyzed. These data can be annotated or graphed directly. Analysis is saved, and the graph and corresponding data can be exported. For additional analysis, Dexterity provides access to custom scripts created by other users.

RESULTS

To determine the utility of Dexterity, we performed a study to evaluate the effects of task difficulty on the degree of impairment after injury. Dexterity analyzed two months of data and allowed new users to annotate the experiment, visualize results, and save and export data easily.

COMPARISON WITH EXISTING METHOD(S)

Previous analysis of tasks was performed with custom data analysis, requiring expertise with analysis software. Dexterity made the tools required to analyze, visualize and annotate data easy to use by investigators without data science experience.

CONCLUSIONS

Dexterity increases accessibility to automated tasks that measure dexterity by making analysis of large data intuitive, robust, and efficient.

A Novel Rodent Orthotopic Forelimb Transplantation Model That Allows for Reliable Assessment of Functional Recovery Resulting From Nerve Regeneration

Improved nerve regeneration and functional outcomes would greatly enhance the utility of vascularized composite allotransplantation (VCA) such as hand and upper extremity transplantation. However, research aimed at achieving this goal has been limited by the lack of a functional VCA animal model. We have developed a novel rat midhumeral forelimb transplant model that allows for the characterization of upper extremity functional recovery following transplantation. At the final end point of 12 weeks, we found that animals with forelimb transplantation including median, ulnar and radial nerve coaptation demonstrated significantly improved grip strength and forelimb function as compared to forelimb transplantation without nerve approximation (grip strength: 1.71N ± 0.57 vs. no appreciable recovery; IBB scale: 2.6 ± 0.7? vs. 0.8 ± 0.40; p = 0.0005), and similar recovery to nerve transection-and-repair only (grip strength: 1.71N ± 0.57 vs. 2.03 ± 0.42.6; IBB scale: 2.6 ± 0.7 vs. 2.8 ± 0.8; p = ns). Moreover, all forelimb transplant animals with nerve coaptation displayed robust axonal regeneration with myelination and reduced flexor muscle atrophy when compared to forelimb transplant animals without nerve coaptation. In conclusion, this is the first VCA small-animal model that allows for reliable and reproducible measurement of behavioral functional recovery in addition to histologic evaluation of nerve regeneration and graft reinnervation.

The supination assessment task: An automated method for quantifying forelimb rotational function in rats

BACKGROUND

Neurological injuries or disease can impair the function of motor circuitry controlling forearm supination, and recovery is often limited. Preclinical animal models are essential tools for developing therapeutic interventions to improve motor function after neurological damage. Here we describe the supination assessment task, an automated measure of quantifying forelimb supination in the rat.

NEW METHOD

Animals were trained to reach out of a slot in a cage, grasp a spherical manipulandum, and supinate the forelimb. The angle of the manipulandum was measured using a rotary encoder. If the animal exceeded the predetermined turn angle, a reward pellet was delivered. This automated task provides a large, high-resolution dataset of turn angle over time. Multiple parameters can be measured including success rate, peak turn angle, turn velocity, area under the curve, and number of rotations per trial. The task provides a high degree of flexibility to the user, with both software and hardware parameters capable of being adjusted.

RESULTS

We demonstrate the supination assessment task can effectively measure significant deficits in multiple parameters of rotational motor function for multiple weeks in two models of ischemic stroke.

COMPARISON WITH EXISTING METHODS

Preexisting motor assays designed to measure forelimb supination in the rat require high-speed video analysis techniques. This operant task provides a high-resolution, quantitative end-point dataset of turn angle, which obviates the necessity of video analysis.

CONCLUSIONS

The supination assessment task represents a novel, efficient method of evaluating forelimb rotation and may help decrease the cost and time of running experiments.

A Within-Animal Comparison of Skilled Forelimb Assessments in Rats

A variety of skilled reaching tasks have been developed to evaluate forelimb function in rodent models. The single pellet skilled reaching task and pasta matrix task have provided valuable insight into recovery of forelimb function in models of neurological injury and disease. Recently, several automated measures have been developed to reduce the cost and time burden of forelimb assessment in rodents. Here, we provide a within-subject comparison of three common forelimb assessments to allow direct evaluation of sensitivity and efficiency across tasks. Rats were trained to perform the single pellet skilled reaching task, the pasta matrix task, and the isometric pull task. Once proficient on all three tasks, rats received an ischemic lesion of motor cortex and striatum to impair use of the trained limb. On the second week post-lesion, all three tasks measured a significant deficit in forelimb function. Performance was well-correlated across tasks. By the sixth week post-lesion, only the isometric pull task measured a significant deficit in forelimb function, suggesting that this task is more sensitive to chronic impairments. The number of training days required to reach asymptotic performance was longer for the isometric pull task, but the total experimenter time required to collect and analyze data was substantially lower. These findings suggest that the isometric pull task represents an efficient, sensitive measure of forelimb function to facilitate preclinical evaluation in models of neurological injury and disease.

An automated task for the training and assessment of distal forelimb function in a mouse model of ischemic stroke

BACKGROUND

Behavioral models relevant to stroke research seek to capture important aspects of motor skills typically impaired in human patients, such as coordination of distal musculature. Such models may focus on mice since many genetic tools are available for use only in that species and since the training and behavioral demands of mice can differ from rats even for superficially similar behavioral readouts. However, current mouse assays are time consuming to train and score, especially in a manner producing continuous quantification. An automated assay of mouse forelimb function may provide advantages for quantification and speed, and may be useful for many applications including stroke research.

NEW METHOD

We present an automated assay of distal forelimb function. In this task, mice reach forward, grip and pull an isometric handle with a prescribed force. The apparatus partially automates the training process so that mice can be trained quickly and simultaneously.

RESULTS

Using this apparatus, it is possible to measure long-lasting impairment in success rate, force pulled, latency to pull, and latency to success up to 22 weeks following photothrombotic cortical strokes in mice.

COMPARISON WITH EXISTING METHOD(S)

This assessment measures forelimb function as do pellet reach tasks, but it utilizes a different motion and provides automatic measures that can ease and augment the research process.

CONCLUSIONS

This high-throughput behavioral assay can detect long-lasting motor impairments, eliminates the need for subjective scoring, and produces a rich, continuous data set from which many aspects of the reach and grasp motion can be automatically extracted.

Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation

Despite many prior studies demonstrating offline behavioral gains in motor skills after sleep, the underlying neural mechanisms remain poorly understood. To investigate the neurophysiological basis for offline gains, we performed single-unit recordings in motor cortex as rats learned a skilled upper-limb task. We found that sleep improved movement speed with preservation of accuracy. These offline improvements were linked to both replay of task-related ensembles during non-rapid eye movement (NREM) sleep and temporal shifts that more tightly bound motor cortical ensembles to movements; such offline gains and temporal shifts were not evident with sleep restriction. Interestingly, replay was linked to the coincidence of slow-wave events and bursts of spindle activity. Neurons that experienced the most consistent replay also underwent the most significant temporal shift and binding to the motor task. Significantly, replay and the associated performance gains after sleep only occurred when animals first learned the skill; continued practice during later stages of learning (i.e., after motor kinematics had stabilized) did not show evidence of replay. Our results highlight how replay of synchronous neural activity during sleep mediates large-scale neural plasticity and stabilizes kinematics during early motor learning.

During non-REM sleep in rats, consolidation and offline improvements of a recently learned motor skill are linked to synchronous reactivation of task-related neural ensembles.

Sleep has been shown to help in consolidating learned motor tasks. In other words, sleep can induce “offline” gains in a new motor skill even in the absence of further training. However, how sleep induces this change has not been clearly identified. One hypothesis is that consolidation of memories during sleep occurs by “reactivation” of neurons engaged during learning. In this study, we tested this hypothesis by recording populations of neurons in the motor cortex of rats while they learned a new motor skill and during sleep both before and after the training session. We found that subsets of task-relevant neurons formed highly synchronized ensembles during learning. Interestingly, these same neural ensembles were reactivated during subsequent sleep blocks, and the degree of reactivation was correlated with several metrics of motor memory consolidation. Specifically, after sleep, the speed at which animals performed the task while maintaining accuracy was increased, and the activity of the neuronal assembles were more tightly bound to motor action. Further analyses showed that reactivation events occurred episodically and in conjunction with spindle-oscillations—common bursts of brain activity seen during sleep. This observation is consistent with previous findings in humans that spindle-oscillations correlate with consolidation of learned tasks. Our study thus provides insight into the neuronal network mechanism supporting consolidation of motor memory during sleep and may lead to novel interventions that can enhance skill learning in both healthy and injured nervous systems.

Robust neuroprosthetic control from the stroke perilesional cortex

Intracortical brain-machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke.